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Spatial population genetics in heavily managed species: Separating patterns of historical translocation from contemporary gene flow in white-tailed deer.
- Source :
-
Evolutionary applications [Evol Appl] 2021 May 04; Vol. 14 (6), pp. 1673-1689. Date of Electronic Publication: 2021 May 04 (Print Publication: 2021). - Publication Year :
- 2021
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Abstract
- Approximately 100 years ago, unregulated harvest nearly eliminated white-tailed deer ( Odocoileus virginianus ) from eastern North America, which subsequently served to catalyze wildlife management as a national priority. An extensive stock-replenishment effort soon followed, with deer broadly translocated among states as a means of re-establishment. However, an unintended consequence was that natural patterns of gene flow became obscured and pretranslocation signatures of population structure were replaced. We applied cutting-edge molecular and biogeographic tools to disentangle genetic signatures of historical management from those reflecting spatially heterogeneous dispersal by evaluating 35,099 single nucleotide polymorphisms (SNPs) derived via reduced-representation genomic sequencing from 1143 deer sampled statewide in Arkansas. We then employed Simpson's diversity index to summarize ancestry assignments and visualize spatial genetic transitions. Using sub-sampled transects across these transitions, we tested clinal patterns across loci against theoretical expectations of their response under scenarios of re-colonization and restricted dispersal. Two salient results emerged: (A) Genetic signatures from historic translocations are demonstrably apparent; and (B) Geographic filters (major rivers; urban centers; highways) now act as inflection points for the distribution of this contemporary ancestry. These results yielded a statewide assessment of contemporary population structure in deer as driven by historic translocations as well as ongoing processes. In addition, the analytical framework employed herein to effectively decipher extant/historic drivers of deer distribution in Arkansas is also applicable for other biodiversity elements with similarly complex demographic histories.<br />Competing Interests: None declared.<br /> (© 2021 The Authors. Evolutionary Applications published by John Wiley & Sons Ltd.)
Details
- Language :
- English
- ISSN :
- 1752-4571
- Volume :
- 14
- Issue :
- 6
- Database :
- MEDLINE
- Journal :
- Evolutionary applications
- Publication Type :
- Academic Journal
- Accession number :
- 34178112
- Full Text :
- https://doi.org/10.1111/eva.13233